A Quick Guide to Data Visualization

A Quick Guide to Data Visualization

A Quick Guide to Data Visualization

The growing significance of big data and the insight it imparts is of utmost significance. Data scientists are working round the clock to process the massive amount of data generated every day. However, unless you have been through Data Science training, it would be impossible for you to grasp even an iota of what is being communicated through data.

The patterns, outliers every single important factor that emerged through decoding must be presented in a coherent format for the untrained eyes. Data visualization enables the researchers to present data findings visually via different techniques and tools to enable people to grasp that information easily.

Why data visualization is so vital?

The complicated nuances of data analysis is not easier for anybody to understand. As we humans are programmed to gravitate towards a visual representation of any information, it makes sense to convey the findings through charts, graphs, or, some other way. This way it takes only a couple of moments for the marketing heads to process what is the trend to watch out for. 

We are used to seeing and processing the information presented through bars and pie charts in company board meetings, people use these conventional models to represent company sales data.

It only makes sense to narrate what the scientists have gathered from analyzing complex raw data sets, via visual techniques to an audience who needs that information to form data-driven decisions for the future.

So what are the different formats and tools of data visualization?

Data visualization can take myriad forms which may vary in the format but, these all have one purpose to serve representing data in an easy to grasp manner. The data scientist must be able to choose the right technique to relate his data discovery which should not only enlighten the audience but, also entertain them.

The popular data visualization formats are as follows

Area Chart
Bubble Cloud/Chart
 Scatter Plot
Funnel Chart
Heat Map
The formats should be adopted in accordance with the information to be communicated

Data scientists also have access to smart visualization tools which are

  • Qlikview
  • Datawrapper
  • Sisense
  • FusionCharts
  • Plotly
  • Looker
  • Tableau

A data scientist must be familiar with the tools available and be able to decide on which suits his line of work better.

What are the advantages of data visualization?

Data visualization is a tricky process while ensuring that the audience does not fall asleep during a presentation, data scientists also need to identify the best visualization techniques, which they can learn during big data training in gurgaon to represent the relationship, comparison or, some other data dynamic.
If and when done right data visualization  has several benefits to offer

Enables efficient analysis of data

In business, efficient data interpretation can help companies understand trends. Data visualization allows them quickly identify and grasp the information regarding company performance hidden in the data and enables them to make necessary changes to the strategy.

Identify connections faster

While representing information regarding the operational issues of an organization,  data visualization technique can be of immense help as it allows to show connections among different data sets with more clarity. Thereby enabling the management to quickly identify the connecting factors. 

Better performance analysis

Using certain visualizing techniques it is easier to present a product or, customer-related data in a multi-dimensional manner. This could provide the marketing team with the insight to understand the obstacles they are facing. Such as the reaction of a certain demographic to a particular product, or, it could also be the demand for certain products in different areas.  They are able to act faster to solve the niggling issues this way.

Adopt the latest trends

 Data processing can quickly identify the emerging trends, and with the help of data visualization techniques, the findings could be quickly represented in an appealing manner to the team. The visual element can immediately communicate which trends are to watch out for and which might no longer work.

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 Encourages interaction

Visual representation of data allows the strategists to not just look at numbers but, actually understand the story being told through the patterns. It encourages interaction and allows them to delve deeper into the patterns, instead of just merely looking at some numbers and making assumptions.

Data visualization is certainly aiding the businesses to gain an insight that was lost to them earlier. A data scientist needs to be familiar with the sophisticated data visualization tools and must strike a balance between the data and its representation. Identifying what is unimportant and which needs to be communicated as well as finding an engaging visual technique to quickly narrate the story is what makes him an asset for the company.  A premier Data analyst training institute can help hone the skills of an aspiring data scientist through carefully designed courses.



July 28, 2020 6:05 pm Published by , , , , , , , ,

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